From my sudoku solver algorithm http://sudoku.connotech.com, I made a puzzle design method, all handcrafted in the sense that it uses no computer generated random numbers. This method is still unpolished, but I guess I am getting a reasonable scheme.

Here is the latest outcome (my first use of the latest refinement in the method):

From my sudoku solver algorithm http://sudoku.connotech.com, I made a puzzle design method, all handcrafted in the sense that it uses no computer generated random numbers. This method is still unpolished, but I guess I am getting a reasonable scheme.

Here is the latest outcome (my first use of the latest refinement in the method):

The designer starts with a blank grid, fills in clues incrementally reducing the set of solutions from1) huge to many, and then either2a) from many to one or2b) from many to none.3) Once the step 2a) is completed, it may be useful to remove extra clues (if any) from the puzzle.

Clues selection is manual, the software reports data (presumably) having the potential to assist the designer in selecting clues depending on what is intended.

In the above first noteworthy experiment (with new step 2a-2b), I just wanted to complete the design cycle. Thus, a small number of clues was a favorable outcome.

Now online is the solver and the step 3) which can be used to turn a puzzle with extra clues into a harder one. The step 1) is somehow on-line but lacks relevant summary statistics.

Transition from step 1 to 2a-2b may require an intermediate step 1.5. It's a matter of making things not too compute-intensive. The step 2a-2b computes every possible solutions for the puzzle-in-progress, yet it is not too compute-intensive for samples from the hard puzzle list from which two or three clues are removed (the exploit would be to remove three clues, then add only two and get a valid puzzle).

Such process can help somebody to get a feeling on the structure of valid puzzles.

Most of the persons working in that field are considering millions of puzzles (I commonly generate 10 millions of puzzles in a day)

This can not be done in a manual process.

May be it would be necessary to identify clearly who can be interested buy such a process knowing that all solvers gives already some possibilities to build a valid puzzle just using the validity check.

You can, for example fill manually a grid using Sudoku Explainer an check, step by step if you got a valid puzzle.

The intriguing feature is to show the structure of an ideal puzzle (i.e. no extra clue) by removing any clue. Some hard puzzles seems to always have a unique way of coming back to a valid puzzle (re-inserting the removed clue), but other puzzles may be quite different. For instance, starting from this multiple-solution-clue-set

May be it would be necessary to identify clearly who can be interested buy such a process knowing that all solvers gives already some possibilities to build a valid puzzle just using the validity check.

Basically, I developed an efficient sudoku solver core and I used it as an example/milestone in the web server project. Since a sudoku solver is not attractive these days, I felt the need to include this puzzle characterization slant. But at the same time, I do not want to give away cpu cycles, thus I refrain from e.g. automated searches for fewer clues in a given puzzle.

So, the basic answer is puzzle generation algorithm designers may use the characterization capability as an ad-hoc investigation tool.

I have currently no incentive to release the core algorithm (and some minor variations of it) for inclusion into other sudoku software.